The objectives of the Center for Gamma-Ray Imaging are to develop advanced gamma-ray detectors and Imaging systems, to push the limits of spatial and temporal resolution in SPECT and PET, and to make state-of-the-art technology available to our collaborators and to the biomedical research community. Much of the emphasis Is on basic research with animal models, but there are many possibilities for translating the technology and the results of the collaborative research into clinical practice. We strive to integrate the components of the P41 mechanism (core technology development, collaborative research, service, dissemination and training) into a comprehensive program that addresses all aspects of gamma-ray imaging, including the radiopharmaceutical, image formation and detection, data acquisition and processing and the final biomedical application. The core technology projects include development of new gamma-ray and charged-particle detectors with high sensitivity and high spatial and temporal resolution;design and construction of new imaging systems incorporating sophisticated list-mode data-acquisition electronics;rigorous task-based evaluation and optimization of imaging systems and algorithms;design and analysis of adaptive and multimodality systems;and development of new animal models and image-analysis methods for molecular imaging. Collaborative research includes projects in cancer diagnosis and therapy, neurological and cardiovascular disease, stem cells, image science in nuclear medicine, and imaging biomarkers. Dissemination includes supplying imaging hardware and software to our collaborators, as well as workshops and a web site for traditional dissemination of information. Training includes both formal short courses and hands-on training in Tucson for our collaborators. Service includes performing routine animal studies, testing and calibrating detectors and detector materials, and providing advice on image quality.
The instruments and methods developed by the Center will provide better tools for investigators studying preclinical animal models of important diseases such as cancer, cardiovascular disease and stroke, and neurologic disorders. As the methods become incorporated into clinical imaging systems, they will have a direct impact on improved diagnosis and management of these disorders.
| Henscheid, Nick; Clarkson, Eric; Myers, Kyle J et al. (2018) Physiological random processes in precision cancer therapy. PLoS One 13:e0199823 |
| Ruiz-Gonzalez, Maria; Bora, Vaibhav; Furenlid, Lars R (2018) Maximum-Likelihood Estimation of Scintillation Pulse Timing. IEEE Trans Radiat Plasma Med Sci 2:1-6 |
| Papachristou, Maria; Kastis, George A; Stavrou, Petros Z et al. (2018) Radiolabeled methotrexate as a diagnostic agent of inflammatory target sites: A proof-of-concept study. Mol Med Rep 17:2442-2448 |
| Li, Xin; Ruiz-Gonzalez, Maria; Furenlid, Lars R (2018) An edge-readout, multilayer detector for positron emission tomography. Med Phys 45:2425-2438 |
| Ghanbari, Nasrin; Clarkson, Eric; Kupinski, Matthew et al. (2017) Optimization of an Adaptive SPECT System with the Scanning Linear Estimator. IEEE Trans Radiat Plasma Med Sci 1:435-443 |
| Ding, Yijun; Caucci, Luca; Barrett, Harrison H (2017) Null functions in three-dimensional imaging of alpha and beta particles. Sci Rep 7:15807 |
| Ding, Yijun; Caucci, Luca; Barrett, Harrison H (2017) Charged-particle emission tomography. Med Phys 44:2478-2489 |
| Dickinson, Sally E; Janda, Jaroslav; Criswell, Jane et al. (2016) Inhibition of Akt Enhances the Chemopreventive Effects of Topical Rapamycin in Mouse Skin. Cancer Prev Res (Phila) 9:215-24 |
| Clarkson, Eric; Barrett, Harrison H (2016) Characteristic functionals in imaging and image-quality assessment: tutorial. J Opt Soc Am A Opt Image Sci Vis 33:1464-75 |
| Clarkson, Eric; Cushing, Johnathan B (2016) Shannon information for joint estimation/detection tasks and complex imaging systems. J Opt Soc Am A Opt Image Sci Vis 33:286-92 |
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